category
bioRxiv
date
Mar 28, 2026
slug
status
Published
summary
提出开源的Openfish库和Slorado框架,突破纳米孔测序碱基识别的硬件限制,实现跨异构计算环境的高性能碱基识别,支持DNA/RNA且精度与商业软件Dorado相当。
tags
测序技术
type
Post

📄 原文题目

Open-source, Hardware-Independent GPU Acceleration for Scalable Nanopore Basecalling with Slorado and Openfish

🔗 原文链接

💡 AI 核心解读

提出开源的Openfish库和Slorado框架,突破纳米孔测序碱基识别的硬件限制,实现跨异构计算环境的高性能碱基识别,支持DNA/RNA且精度与商业软件Dorado相当。

📝 英文原版摘要

Nanopore sequencing technologies are used widely in genomics research and their adoption continues to accelerate. 'Basecalling' is an essential step in the nanopore sequencing workflow, during which raw electrical signals are translated into nucleotide sequences. The current state-of-the-art basecaller, Oxford Nanopore Technologies (ONT) software 'Dorado,' relies on proprietary, platform-specific NVIDIA GPU optimisations bundled in the closed-source 'Koi' library. As a result, practical, high-speed basecalling is effectively restricted to a narrow class of supported hardware, limiting accessibility, portability, and innovation. We present (1) 'Openfish,' an open-source GPU-accelerated nanopore basecaller decoding library that provides a competitive alternative to ONT's proprietary Koi library; and (2) Slorado, a fully open-source basecalling framework that supports both DNA and RNA with equivalent accuracy to Dorado. Together, Openfish and Slorado remove the hardware lock-in that currently limits high-performance nanopore basecalling. Our framework scales efficiently across heterogeneous computing environments, from low-power embedded devices to GPU-equipped datacenters, without sacrificing speed or accuracy. Openfish and Slorado are available as free open-source packages for basecalling research, optimisation and deployment beyond the constraints of proprietary software and hardware ecosystems: Openfish: https://github.com/warp9seq/openfish, Slorado: https://github.com/BonsonW/slorado.
前列腺癌的单细胞和空间图谱揭示了谱系可塑性和转移背后基因模块的组合特性去甲肾上腺素能神经元中谷氨酸共释放调控呼吸并在阿片类药物诱导的呼吸抑制中被抑制
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